Add timepoint to data

Calculated sequential timepoint for participants along the 'visit_age' column.

add_timepoint(data, name = timepoint)

Arguments

data	data extracted from the NOAS
name	unquoted name to give the new column

Value

data frame with extra column with timepoint

Examples

# attach built-in noas example data to test
dt <- noas_example

add_timepoint(dt)
#> # A tibble: 10 x 9
#> # Groups:   subject_id [2]
#>    subject_id project_id wave_code site_name mri_info_folder visit_age   cog
#>    <chr>      <chr>          <dbl> <chr>     <chr>               <dbl> <dbl>
#>  1 1000000    MemP               1 ousAvanto 1000000_1               8    16
#>  2 1000000    MemP               2 ousAvanto 1000000_2              10    14
#>  3 1000000    MemP               3 ousAvanto 1000000_3              14    16
#>  4 1000000    MemP               3 ousSkyra  1000000_4              14    NA
#>  5 1000000    MemP               4 ousSkyra  1000000_5              17    15
#>  6 1000000    MemP               5 ousSkyra  1000000_6              20    15
#>  7 1000010    MemC               1 ousSkyra  1000010_1              22    14
#>  8 1000010    MemC               2 ousSkyra  1000010_2              28    13
#>  9 1000010    MemC               3 ousSkyra  1000010_3              33    NA
#> 10 1000010    MemC               4 ousSkyra  1000010_4              40    10
#> # … with 2 more variables: sex <chr>, timepoint <dbl>

library(dplyr)
dt %>%
 add_timepoint()
#> # A tibble: 10 x 9
#> # Groups:   subject_id [2]
#>    subject_id project_id wave_code site_name mri_info_folder visit_age   cog
#>    <chr>      <chr>          <dbl> <chr>     <chr>               <dbl> <dbl>
#>  1 1000000    MemP               1 ousAvanto 1000000_1               8    16
#>  2 1000000    MemP               2 ousAvanto 1000000_2              10    14
#>  3 1000000    MemP               3 ousAvanto 1000000_3              14    16
#>  4 1000000    MemP               3 ousSkyra  1000000_4              14    NA
#>  5 1000000    MemP               4 ousSkyra  1000000_5              17    15
#>  6 1000000    MemP               5 ousSkyra  1000000_6              20    15
#>  7 1000010    MemC               1 ousSkyra  1000010_1              22    14
#>  8 1000010    MemC               2 ousSkyra  1000010_2              28    13
#>  9 1000010    MemC               3 ousSkyra  1000010_3              33    NA
#> 10 1000010    MemC               4 ousSkyra  1000010_4              40    10
#> # … with 2 more variables: sex <chr>, timepoint <dbl>

# Change the name of the variable
dt %>%
 add_timepoint(name = tp)
#> # A tibble: 10 x 9
#> # Groups:   subject_id [2]
#>    subject_id project_id wave_code site_name mri_info_folder visit_age   cog
#>    <chr>      <chr>          <dbl> <chr>     <chr>               <dbl> <dbl>
#>  1 1000000    MemP               1 ousAvanto 1000000_1               8    16
#>  2 1000000    MemP               2 ousAvanto 1000000_2              10    14
#>  3 1000000    MemP               3 ousAvanto 1000000_3              14    16
#>  4 1000000    MemP               3 ousSkyra  1000000_4              14    NA
#>  5 1000000    MemP               4 ousSkyra  1000000_5              17    15
#>  6 1000000    MemP               5 ousSkyra  1000000_6              20    15
#>  7 1000010    MemC               1 ousSkyra  1000010_1              22    14
#>  8 1000010    MemC               2 ousSkyra  1000010_2              28    13
#>  9 1000010    MemC               3 ousSkyra  1000010_3              33    NA
#> 10 1000010    MemC               4 ousSkyra  1000010_4              40    10
#> # … with 2 more variables: sex <chr>, tp <dbl>